• DocumentCode
    3586624
  • Title

    Speeding-up image processing in reaction-diffusion cellular neural networks using CUDA-enabled GPU platforms

  • Author

    Stoica, George Valentin ; Dogaru, Radu ; Stoica, Elena Cristina

  • Author_Institution
    Dept. of Appl. Electron. & Inf. Eng., Univ. “Politeh.” of Bucharest, Bucharest, Romania
  • fYear
    2014
  • Firstpage
    39
  • Lastpage
    42
  • Abstract
    Due to their inherent architecture, the discrete time model of Cellular nonlinear networks (CNNs) for image processing are well suited candidates for efficient implementation using massively parallel architectures. This paper proposes an implementation model for GPU architectures and highlights the advantages over the CPU version, using nVidia´s CUDA platform.
  • Keywords
    cellular neural nets; image processing; parallel architectures; CNN; CUDA-enabled GPU platforms; GPU architectures; massively parallel architectures; reaction-diffusion cellular neural networks; speeding-up image processing; Computational modeling; Computer architecture; Graphics processing units; Hardware; Image processing; Instruction sets; Parallel processing; CUDA-enabled GPU; nonlinear image processing; reaction-diffusion CNN;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics, Computers and Artificial Intelligence (ECAI), 2014 6th International Conference on
  • Print_ISBN
    978-1-4799-5478-0
  • Type

    conf

  • DOI
    10.1109/ECAI.2014.7090162
  • Filename
    7090162
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3586624